Add to ORKGA multivariate approach for integrating genome-wide expression data and biological knowledg
Goesmann A, Linke B, Rupp O, et al. Building a BRIDGE for the integration of heterogeneous data from...
Multivariate methods and software for association mapping in dose-response genome-wide association s...
Background: To leverage the potential of multi-omics studies, exploratory data analysis methods that...
The rise of Big Data has enabled sophisticated analysis of the human genome in unprecedented detail....
Exploring the functional landscape of gene expression: directed search of large microarray compendi
Modern next-generation sequencing and microarray-based assays have empowered the computational biolo...
Multi-view learning is the branch of machine learning that deals with multi modal data, i.e. with pa...
Interpreting results provided by multivariate exploratory methods (such as Principal Component Analy...
Recent advances in various forms of omics technologies have generated huge amount of data. To fully ...
Exploiting sample variability to enhance multivariate analysis of microarray dat
In biomedical research, it has become common to collect data that measures biological functions in d...
We address the problem of using expression data and prior biological knowledge to identify different...
The functional analysis of genes using genomes is a major research issue in modern biology. Function...
Motivation: A rapid technological development in the biosciences and in computer science in the last...
Scientific research in bio-informatics is often data-driven and supported by numerous biological dat...
Goesmann A, Linke B, Rupp O, et al. Building a BRIDGE for the integration of heterogeneous data from...
Multivariate methods and software for association mapping in dose-response genome-wide association s...
Background: To leverage the potential of multi-omics studies, exploratory data analysis methods that...
The rise of Big Data has enabled sophisticated analysis of the human genome in unprecedented detail....
Exploring the functional landscape of gene expression: directed search of large microarray compendi
Modern next-generation sequencing and microarray-based assays have empowered the computational biolo...
Multi-view learning is the branch of machine learning that deals with multi modal data, i.e. with pa...
Interpreting results provided by multivariate exploratory methods (such as Principal Component Analy...
Recent advances in various forms of omics technologies have generated huge amount of data. To fully ...
Exploiting sample variability to enhance multivariate analysis of microarray dat
In biomedical research, it has become common to collect data that measures biological functions in d...
We address the problem of using expression data and prior biological knowledge to identify different...
The functional analysis of genes using genomes is a major research issue in modern biology. Function...
Motivation: A rapid technological development in the biosciences and in computer science in the last...
Scientific research in bio-informatics is often data-driven and supported by numerous biological dat...
Goesmann A, Linke B, Rupp O, et al. Building a BRIDGE for the integration of heterogeneous data from...
Multivariate methods and software for association mapping in dose-response genome-wide association s...
Background: To leverage the potential of multi-omics studies, exploratory data analysis methods that...